code: def forward_cpu(self, x):
      global _ndtr_cpu
      if _ndtr_cpu is None:
          try:
              from scipy import special
  
              _ndtr_cpu = special.ndtr
          except ImportError:
              warnings.warn(
                  "SciPy is not available. Forward computation of ndtr in"
                  " CPU can be slow without SciPy.",
                  chainer.warnings.PerformanceWarning,
              )
              _ndtr_cpu = numpy.vectorize(_slow_ndtr_cpu)
      self.retain_inputs((0,))
      return (utils.force_array(_ndtr_cpu(x[0]), dtype=x[0].dtype),)
  
file_path: chainer/chainer/functions/math/ndtr.py
imports: import math
  import warnings
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.functions.math import exponential
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the Ndtr obj's underlying member method code with example usage: obj.forward_cpu(x) and returns: utils